A New Method to Predict the Popularity of the Microblog

Abstract

This paper proposes a new approach to predict the popularity of content in the Chinese microblogging website Sina Weibo. There are four operations in Sina Weibo, including post, repost-only, repost-and-comment, and comment-only. We model these operations as a bipartite graph, which takes the temporal factor into account by assigning edge weight as an exponential decay function. We then propose a regularization framework on this model to predict the original post's future popularity. Experimental results show that our method outperforms other methods in predicting the post's future popularity, especially for shortterm prediction.